REVIEW ON: ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY AND DEVELOPMENT

Abstract

Artificial Intelligence (AI) focuses in producing intelligent modelling, which helps in imagining knowledge, cracking problems and decision making. Recently, AI plays an important role in various fields of pharmacy like drug discovery, drug development process, pharmaceutical manufacturing, quality control and quality assurance etc. In drug discovery, AI accelerates the identification of potential drug candidates by analysing vast datasets, predicting molecular interactions, and optimizing lead compounds. During the drug development process, AI aids in clinical trial design, patient stratification, and predicting drug safety and efficacy, significantly reducing time and cost. In pharmaceutical manufacturing, AI enables process optimization, predictive maintenance, and quality control, ensuring consistent and high-quality production. AI also plays a pivotal role in detection technologies, facilitating early disease diagnosis, biomarker identification, and monitoring therapeutic responses. Furthermore, AI addresses current pharmaceutical challenges, including complex regulatory requirements, high attrition rates, and the need for personalized medicine. While the advantages of AI include faster timelines, cost savings, improved accuracy, and data-driven decision-making, disadvantages such as data quality issues, ethical concerns, over-reliance on algorithms, and regulatory hurdles must be carefully managed. Overall, AI is poised to revolutionize the pharmaceutical landscape, offering transformative potential while requiring thoughtful implementation.